Struct MultiModalFeatureSelector 

pub struct MultiModalFeatureSelector<State = Untrained> { /* private fields */ }

Multi-modal feature selector for heterogeneous data types.

This selector handles feature selection across multiple data modalities using various fusion strategies. It can analyze cross-modal relationships, handle missing modalities, and apply different selection criteria for each modality type.

Implementations

impl MultiModalFeatureSelector<Untrained>

pub fn new() -> Self

Creates a new MultiModalFeatureSelector with default parameters.

pub fn builder() -> MultiModalFeatureSelectorBuilder

Creates a builder for configuring the MultiModalFeatureSelector.

Trait Implementations

impl<State: Clone> Clone for MultiModalFeatureSelector<State>

fn clone(&self) -> MultiModalFeatureSelector<State>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<State: Debug> Debug for MultiModalFeatureSelector<State>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for MultiModalFeatureSelector<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for MultiModalFeatureSelector<Untrained>

type Config = ()

Configuration type for the estimator

type Error = SklearsError

Error type for the estimator

type Float = f64

The numeric type used by this estimator

fn config(&self) -> &Self::Config

Get estimator configuration

fn validate_config(&self) -> Result<(), SklearsError>

Validate estimator configuration with detailed error context

fn check_compatibility( &self, n_samples: usize, n_features: usize, ) -> Result<(), SklearsError>

Check if estimator is compatible with given data dimensions

fn metadata(&self) -> EstimatorMetadata

Get estimator metadata

impl Estimator for MultiModalFeatureSelector<Trained>

type Config = ()

Configuration type for the estimator

type Error = SklearsError

Error type for the estimator

type Float = f64

The numeric type used by this estimator

fn config(&self) -> &Self::Config

Get estimator configuration

fn validate_config(&self) -> Result<(), SklearsError>

Validate estimator configuration with detailed error context

fn check_compatibility( &self, n_samples: usize, n_features: usize, ) -> Result<(), SklearsError>

Check if estimator is compatible with given data dimensions

fn metadata(&self) -> EstimatorMetadata

Get estimator metadata

impl Fit<HashMap<String, ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for MultiModalFeatureSelector<Untrained>

type Fitted = MultiModalFeatureSelector<Trained>

The fitted model type

fn fit( self, modalities: &HashMap<String, Array2<f64>>, y: &Array1<f64>, ) -> Result<Self::Fitted>

Fit the model to the provided data with validation

fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>

where Self: Sized,

Fit with custom validation and early stopping

impl Transform<HashMap<String, ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for MultiModalFeatureSelector<Trained>

fn transform( &self, modalities: &HashMap<String, Array2<f64>>, ) -> Result<Array2<f64>>

Transform the input data